I am a Professor of Informatics and Computer Science and the Director of the Center for Complex Networks and Systems Research at the Indiana University School of Informatics and Computing. I also have courtesy appointments in Cognitive Science and Physics, and am affiliated with the Center for Data and Search Informatics and the Biocomplexity Institute. Finally I am a Fellow at the ISI Foundation in Torino, Italy.
Research in my group, NaN, focuses on Web science, social media, social networks, social computing, Web search and data mining, distributed and intelligent Web applications, and modeling of complex information networks.
My calendar is a bit crowded. You may schedule an appointment with Tara Holbrook, our center’s administrative assistant. Or you can try your luck by Doodle MeetMe, email, phone (+1-812-856-1377), fax (+1-812-855-0600), or in person (Informatics East room 314).
Prospective students interested in joining my group, NaN, should look at this and this and this and this and this and this and this and these before contacting me. Then, if still interested, they should apply to one of our PhD programs: Informatics (Complex Systems track), Computer Science, Cognitive Science, or a combination. I am usually unable to respond to inquiries from prospective students unless they have already been admitted to one of these programs.
Latest News from the Blog
One of the goals of the Social Media in Strategic Communication (SMISC) program run by DARPA is to develop tools to support the efforts of human operators to counter misinformation or deception campaigns with truthful information. In advancing toward this goal, the DESPIC team at the Center for Complex Systems and Networks Research (CNetS) presented a demo of a new tool named BotOrNot at the SMISC meeting held in Arlington, Virginia on April 23-25, 2014. BotOrNot (truthy.indiana.edu/botornot) is a tool to automatically detect whether a given Twitter user is a social bot or a human. Trained on Twitter bots collected by our lab and the infolab at Texas A&M University, BotOrNot analyzes over a thousand features from the user’s friendship network, content, and temporal information in real time and predicts the degree to which the account may be a bot. In addition to the demo, the DESPIC team (including colleagues at the University of Michigan and Lockheed Martin ATL) presented several posters on Scalable Architecture for Social Media Observatory, Meme Clustering in Streaming Data, Persuasion Detection in Social Streams, High-Resolution Anomaly Detection in Social Streams, and Early Detection and Analysis of Rumors.
Congratulations to Lilian Weng, who successfully defended her Informatics PhD dissertation titled Information diffusion on online social networks. The thesis provides insights into information diffusion on online social networks from three aspects: people who share information, features of transmissible content, and the mutual effects between network structure and diffusion process. The first part delves into the limited human attention. The second part of Dr. Weng’s dissertation investigates properties of transmissible content, particularly into the topic space. Finally, the thesis presents studies of how network structure, particularly community structure, influences the propagation of Internet memes and how the information flow in turn affects social link formation. Dr. Weng’s work can contribute to a better and more comprehensive understanding of information diffusion among online social-technical systems and yield applications to viral marketing, advertisement, and social media analytics. Congratulations from her colleagues and committee members: Alessandro Flammini, YY Ahn, Steve Myers, and Fil Menczer!
On August 11, 2013, the New York Times published an article by Ian Urbina with the headline: I Flirt and Tweet. Follow Me at #Socialbot. The article reports on how socialbots (software simulating people on social media) are being designed to sway elections, to influence the stock market, even to flirt with people and one another. Fil Menczer is quoted: “Bots are getting smarter and easier to create, and people are more susceptible to being fooled by them because we’re more inundated with information.” The article also mentions the Truthy project and some of our 2010 findings on political astroturf.
Inspired by this, the writers of The Good Wife consulted with us on an episode in which the main character finds that a social news site is using a socialbot to bring traffic to the site, defaming her client. The episode aired on November 24, 2013, on CBS (Season 5 Episode 9, “Whack-a-Mole”). Good show!
ACM, the professional association of computer scientists and computing professionals, announced today that I was named a Distinguished Scientist. Here is the list of other ACM members who got this award. This is a great honor and I am grateful. But my thanks go especially to my many amazing collaborators (colleagues, postdocs, visiting scholars, and especially students) without whom my contributions and impact would not exist — this award is also yours!
And while I am bragging, let me also mention that I was recently named a Senior Research Fellow of The Kinsey Institute for Research in Sex, Gender, and Reproduction. This is another great honor and I am excited about our team’s collaboration with the Kinsey Institute on the Kinsey Reporter project. The Kinsey Institute has an awesome tradition of trailblazing research and I hope that we can make a small contribution to it. Thanks to both the Kinsey Reporter team and our Kinsey collaborators!
A story in Nature discusses a recent paper (preprint) from CNetS members Jasleen Kaur, Filippo Radicchi and Fil Menczer on the universality of scholarly impact metrics. In the paper, we present a method to quantify the disciplinary bias of any scholarly impact metric. We use the method to evaluate a number of established scholarly impact metrics. We also introduce a simple universal metric that allows to compare the impact of scholars across scientific disciplines. Mohsen JafariAsbagh integrated this metric into Scholarometer, a crowdsourcing system developed by our group to collect and share scholarly impact data. The Nature story highlight how one can use normalized impact metrics to rank all scholars, as illustrated in the widget shown here.
We are excited to announce that the ACM Web Science 2014 Conference will be hosted by our center on the beautiful IUB campus June 23–26, 2014. Web Science studies the vast information network of people, communities, organizations, applications, and policies that shape and are shaped by the Web, the largest artifact constructed by humans in history. Computing, physical, and social sciences come together, complementing each other in understanding how the Web affects our interactions and behaviors. Previous editions of the conference were held in Athens, Raleigh, Koblenz, Evanston, and Paris. The conference is organized on behalf of the Web Science Trust by general co-chairs Fil Menczer, Jim Hendler, and Bill Dutton. Follow us on Twitter and see you in Bloomington!